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Among the numerous advantages of the high-power impulse magnetron sputtering (HiPIMS) technique, the most important is the enhanced ionization degree of sputtered species contributing to the film growth. Consequently, the quality of deposited thin films is highly improved. Still, the optimization process is challenging due to the complexity associated with the intricate transport of the sputtered species, ionized or neutrals. The scarce knowledge available on the spatial distribution of these species when operating a HiPIMS discharge makes the quantitative prediction of any deposition feature particularly difficult. In this paper, we discuss the influence of experimentally controllable quantities, such as gas pressure and target current density, on the transport of sputtered titanium in non-reactive (argon) HiPIMS, namely, on the behavior of metal atoms and metal ion fluxes intercepting the substrate. Systematic quantitative measurements were performed in a diameter normal plane on a circular planar target. Hence, the 2D spatial distribution of the ionized flux fraction (IFF) and the total flux of titanium sputtered particles (deposition rate) are evaluated by biasing a quartz crystal microbalance equipped with an electron magnetic filter. The wide range of parameters we examined allows us to predict and optimize the flux of sputtered species based on complete mapping of the IFF of sputtered particles. [ABSTRACT FROM AUTHOR]

Potato common scab (PCS), a significant potato disease, negatively impacts tuber quality. The present study was conducted to isolate and characterize pathogenic Streptomyces species associated with PCS disease in Türkiye based on their morphological, physiological and molecular characteristics. Field‐grown potatoes that exhibited scab lesions were collected from four provinces in 2020–2021, and 200 bacterial isolates were obtained from netted, superficial and deep‐pitted common scab lesions. Pathogenicity assays, including in vitro tuber slice and in planta radish seedling bioassays, identified 150 pathogenic isolates. Morphological and physiological characterization of 92 selected isolates revealed several Streptomyces species that exhibited diverse mycelium colours, sporulation patterns and pigmentation. Molecular analysis using 16S rRNA sequencing, species‐specific primers, PCR‐RFLP of the 16S‐23S (ITS) region with Hpy99I restriction enzyme, and multilocus sequence analysis (MLSA) based on atpD, recA, rpoB and trpB genes revealed that S. scabiei was the dominant species, followed by S. europaeiscabiei, S. caniscabiei, S. bottropensis, S. stelliscabiei and S. turgidiscabies. PCR analysis revealed the presence of the thaxtomin synthetase genes (txtAB) in all tested samples, while the necrogenic protein (nec1) and tomatinase (tomA)‐encoding genes were absent from three and two isolates, respectively. Phylogenetic analysis of 32 representative isolates conducted with sequences from 16S rRNA, species‐specific PCR and MLSA confirmed their morphological identification and clustered them with reference strains. This study contributes to the understanding of distribution of Streptomyces species associated with PCS, and to our knowledge, is the first molecular confirmation of S. caniscabiei and S. turgidiscabies causing potato scab in Türkiye. [ABSTRACT FROM AUTHOR]

Aim: The potentially cascading consequences of climate changes on redistribution of habitat‐forming species, like seagrasses, remain a major research gap. Empirical demonstrations of local population changes are increasingly reported without a globally integrated predictive framework as a leading testable hypothesis. Therefore, here, we aimed to estimate changes in species richness, community composition, and areas of climatic refugia under future climate scenarios. Location: Global scale. Time Period: Present‐day conditions (from 2010 to 2020) and for three Shared Socioeconomic Pathway (SSP) scenarios of future climate change (from 2090 to 2100). Major Taxa Studies: Seagrasses (plantae). Methods: We coupled seagrass occurrences with environmental predictors (temperature, salinity, nitrate, wave energy, and ice) in stacked species distribution modelling. Results: Models estimated a present global extent of 917,169 km2 with high species richness in Temperate Australasia, Indo‐Pacific, and Temperate North Pacific. Future projections predicted widespread spatial redistribution, with Arctic expansions, losses in lower latitudes, and deeper vertical ranges, while globally maintaining the area extent occupied worldwide by seagrass species (only 5% of change). Species richness increased poleward under more drastic scenarios (SSP3‐7.0 and SSP5‐8.5), with losses in tropical zones (30oN to 30oS). Local climatic refugia are retained in all scenarios but decrease under higher emissions. Additionally, even where seagrass species remain, widespread community composition changes were predicted. Main Conclusions: Our findings serve as baselines to inform, anticipate, and mitigate cascading consequences of shifts in seagrass ecosystems that provide essential services for humanity. [ABSTRACT FROM AUTHOR]

Aim: We aimed to enhance our understanding of the distribution of mesopelagic mesozooplankton (MM) using species distribution models, assess the performance of various modelling techniques, identify key environmental predictors for MM distribution and compute their habitat suitability indices. Location: Our study focused on the mesopelagic zone globally, with data analysed from different oceans. Taxon: Our focus was primarily on mesopelagic mesozooplankton, gathering data on 861 different species from the Mesopelagic Mesozooplankton and Micronekton (MMM) Database. Methods: We used an ensemble of species distribution models, applying 10 different modelling algorithms and three multi‐model ensemble approaches. We explored two important factors that can affect model performance: subsampling and the choice of background points. We also estimated the relative importance of various environmental conditions such as mixed layer depth, temperature, salinity, net primary productivity, euphotic zone depth and dissolved nitrate concentration on the distribution of these species. Results: Euphotic zone depth, salinity and dissolved nitrate concentration were identified as the most important variables for explaining the distribution of mesopelagic mesozooplankton. The ensemble modelling results were robust in areas with abundant observational records, but high uncertainty was observed in data‐limited regions. We found a patchy habitat suitability map for zooplankton when modelled within their native range, largely due to uneven sampling. Unrestricted range models yielded smoother patterns but could inaccurately project species in areas where they do not occur. Main Conclusions: Our study highlights the need for increased sampling effort in data‐limited regions to improve the accuracy of mesopelagic species distribution models. Despite some inaccuracies, unrestricted range models, assuming ecological equivalence (where different species occupying a similar ecological niche in different geographical regions or different ecosystems exhibit similar adaptations and behaviours), provide a reasonable comparison for habitat suitability maps and model performance. It also confirms the significant impact of certain environmental conditions on mesozooplankton distribution. [ABSTRACT FROM AUTHOR]

The Iberian Peninsula and the South of France are a centre of diversification of the Lumbricidae family, which has many endemisms and basal genera in the phylogeny of lumbricids in that area. Two basal and endemic genera of this area are Cataladrilus and Prosellodrilus. These genera are very poorly studied, and there are very few phylogenetic studies in which representatives of these genera have been included. In the case of Prosellodrilus, the type species has never been included in phylogenetic analyses. Therefore, in this study, after capturing specimens of different species of Cataladrilus and Prosellodrilus in their type localities (including the type species of both genera), a phylogenetic analysis was carried out using the molecular markers COI, 16S (mitochondrial) and 28S (nuclear). Sequences from other lumbricid genera obtained in previous studies were also included, with the purpose of testing the monophyly of Prosellodrilus and Cataladrilus and recovering their phylogenetic relationships with other basal genera. As a result, it was possible to demonstrate that both genera are monophyletic and, therefore, valid. Both genera are evolutionarily very close and are found very close to other basal genera such as Castellodrilus and Zophoscolex. Furthermore, by calculating the ancestral area of Prosellodrilus it was possible to observe that the origin of the genus is located in an area between Sardinia and eastern France and that the genus predates the separation of Sardinia from France and the formation of the Pyrenees, which could explain the presence of P. festae in Sardinia and the presence of this genus on both sides of the Pyrenees. Furthermore, if the geological age of the Pyrenees and its formation process are studied in detail, it can be observed how the different stages of formation of this mountain range largely coincide with the distribution of the different species of Prosellodrilus. [ABSTRACT FROM AUTHOR]

The accurate positioning of individual trees, the reconstruction of forest environment in three dimensions and the identification of tree species distribution are crucial aspects of forestry remote sensing. Simultaneous Localization and Mapping (SLAM) algorithms, primarily based on LiDAR or visual technologies, serve as essential tools for outdoor spatial positioning and mapping, overcoming signal loss challenges caused by tree canopy obstruction in the Global Navigation Satellite System (GNSS). To address these challenges, a semantic SLAM algorithm called LVI-ObjSemantic is proposed, which integrates visual, LiDAR, IMU and deep learning at the object level. LVI-ObjSemantic is capable of performing individual tree segmentation, localization and tree spices discrimination tasks in forest environment. The proposed Cluster-Block-single and Cluster-Block-global data structures combined with the deep learning model can effectively reduce the cases of misdetection and false detection. Due to the lack of publicly available forest datasets, we chose to validate the proposed algorithm on eight experimental plots. The experimental results indicate that the average root mean square error (RMSE) of the trajectories across the eight plots is 2.7, 2.8, 1.9 and 2.2 times lower than that of LIO-SAM, FAST-LIO2, LVI-SAM and FAST-LIVO, respectively. Additionally, the mean absolute error in tree localization is 0.12 m. Moreover, the mapping drift of the proposed algorithm is consistently lower than that of the aforementioned comparison algorithms. [ABSTRACT FROM AUTHOR]

Summary: Trait‐based ecology has become a popular phrase. But all species have traits, and their contributions to ecological processes are governed by those traits. So then, is not all ecology trait‐based? Actually, there do exist areas of ecology that are consciously trait‐free, such as neutral theory and species abundance distributions. But much of ecology could be considered actually or potentially trait‐based. A spectrum is described, from trait‐free through trait‐implicit and trait‐explicit to trait‐centric. Trait‐centric ecology includes positioning ecological strategies along trait dimensions, with a view to inferring commonalities and to generalizing from species studied in more detail. Trait‐explicit includes physiological and functional ecology, and areas of community ecology and ecosystem function that invoke traits. Trait‐implicit topics are those where it is important that species are different, but formulations did not initially characterize the differences via traits. Subsequently, strands within these trait‐implicit topics have often moved towards making use of species traits, so the boundary with trait‐explicit is permeable. Trait‐based ecology is productive because of the dialogue between understanding processes in detail, via traits that relate most closely, and generalizing across many species, via traits that can be compared widely. An enduring key question for trait‐based ecology is which traits for which processes. [ABSTRACT FROM AUTHOR]

Climate change is altering the distribution of marine organisms worldwide. This may, in turn, affect the overall structure and functioning of ecosystems, sometimes leading to low productive regimes. Pronounced shifts in distribution and migration have been observed for capelin (Mallotus villosus), one of the ecologically and commercially important species in the Arctic. This study attempts to discern whether a relationship existed between the altered capelin dynamics and the changing physical environmental conditions in the Iceland‐East Greenland‐Jan Mayen region. More specifically, three species distribution models were used to predict hindcasts (pre‐shift years 1993–2002) and nowcasts (post‐shift years 2003–2019) of capelin distribution based on relationships with temperature, salinity, current speed, net primary productivity, and bathymetry. The predicted probability of occurrence over these two time periods demonstrates that the changing environmental conditions have contributed to the modified distribution of the stock during its late feeding season in autumn and during the onset of spawning season in winter. The multi‐model approach used in this study has provided a solid statistical framework to describe the environmental niche of capelin and its potential responses to changing ocean climate. [ABSTRACT FROM AUTHOR]

Understanding how ecosystem change influences fishery resources through trophic pathways is a key tenet of ecosystem‐based fishery management. System models (SM), which use numerical modeling to describe physical and biological processes, can advance inclusion of ecosystem and prey information in fisheries management; however, incorporating SMs in management requires evaluation against empirical data. The Bering Ecosystem Study Nutrient‐Phytoplankton‐Zooplankton (BESTNPZ) model is an SM (originally created by the Bering Ecosystem Study, which initiated in 2006 and was expanded by Kearney et al.) includes zooplankton biomass hindcasts for the Bering Sea. In the Bering Sea, zooplankton are an important prey item for fishery species, yet the zooplankton component of this SM has not been validated against empirical data. We compared empirical zooplankton data to BESTNPZ hindcast estimates for three zooplankton functional groups and found that the two sources of information are on different absolute scales. We found high correlation between relative seasonal biomass trends estimated by BESTNPZ and empirical data for large off‐shelf copepods (Neocalanus spp.) and low correlations for large on‐shelf copepods and small copepods (Calanus spp. and Pseudocalanus spp., respectively). To address these discrepancies, we constructed hybrid species distribution models (H‐SDM), which predict zooplankton biomass using the BESTNPZ hindcast and environmental covariates. We found that H‐SDMs offered marginal improvements over correlative species distribution models (C‐SDMs) relying solely on empirical data for spatial extrapolation and little improvement for most functional groups when forecasting short‐term temporal zooplankton biomass trends. Overall, we suggest that interpretation of current BESTNPZ hindcasts should be tempered by our understanding of key mismatches in absolute scale, seasonality, and annual indices between BESTNPZ and empirical data. [ABSTRACT FROM AUTHOR]

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Map‐based decision support tools (DSTs) that use species distributions are an important means of identifying priority areas for conservation. The Wisconsin Waterfowl Habitat Conservation Strategy (WWHCS) uses a DST to identify priority ecological landscapes and watersheds to guide waterfowl habitat projects. The WWHCS DST relies on waterfowl habitat suitability layers derived through expert opinion in lieu of species distributions, a common approach in DSTs. Given the subjectivity of expert opinion, model‐driven species distributions such as those available from community science projects could provide more reliable information and better identify areas for waterfowl conservation. Here, we explore the application of relative abundance products available through the eBird Status and Trends project as an alternative to expert‐derived habitat suitability layers in the WWHCS DST. Our objectives were to compare seasonal species distributions from habitat suitability models (expert‐derived) and species distribution models (eBird‐derived) and determine whether differences influenced DST prioritizations. Correlations between expert‐ and eBird‐derived distributions were generally low to moderate for breeding and fall layers (ρ: −0.03–0.76), and lowest for spring (ρ: −0.49–0.72). There was also minimal agreement among top‐ranked ecological landscapes (40%) and watersheds (28%) between the two versions of the DST. Finally, we compare tradeoffs and suggest a model‐driven approach for the WWHCS DST. However, additional work validating eBird relative abundance against professional surveys and empirical studies evaluating waterfowl habitat selection and vital rates are important future considerations for the DST and waterfowl habitat conservation in Wisconsin. [ABSTRACT FROM AUTHOR]

Background: Pseudostellaria heterophylla is used in traditional Chinese medicine, so ensuring an adequate supply of plant material with high levels of bioactive components is important. Methods: Using an optimized maximum entropy niche model and assays of bioactive components from cultivation samples, this study started from the plant's natural distribution area and estimated correlations of ecological factors with not only abundance of the plant but also abundance of polysaccharides and heterophyllin B. These correlations were combined with the spatial analysis function in ArcGIS to generate maps of the suitability of different habitats in China for cultivating P. heterophylla under current climate conditions and different models of climate change. Results: The following ecological factors emerged as particularly important for habitat suitability: precipitation of driest month and driest quarter, annual precipitation, annual mean temperature, temperature seasonality, and mean temperature of coldest quarter, contributing to a cumulative total of 87%. Under current climate conditions, optimum habitats of P. heterophylla were mainly distributed in the southwestern region (Guizhou) and eastern regions (Anhui, Zhejiang, Fujian, Jiangsu) of China, and only 0.197×106 km2 of these areas were optimum habitat. In future climate change scenarios, the optimal habitat area of P. heterophylla exhibited an increase across different time periods under the SSP5-8.5 climate scenario. By the 2090s, distribution area of high heterophyllin B content under SSP5-8.5 climate scenarios will increase significantly, distribution area of high polysaccharide content had little change under all three climate scenarios (SSP 1-2.6, 2-4.5, 5-8.5). The center of mass of suitable habitat migrates southwestward under scenario SSP 1-2.6 and SSP 2-4.5, while it migrates northward under scenario SSP 5-8.5. Under the three climate scenarios, the center of mass of suitable habitat migrated consistently with that of high polysaccharide content but differed from that of high heterophyllin B content. Conclusion: These findings provide a crucial foundation for cultivating P. heterophylla with superior medicinal properties, developing adaptive management strategies to enhance conservation efforts, and ensuring sustainable utilization in the face of global climate change. [ABSTRACT FROM AUTHOR]

Quickly locating new populations of non‐native species can reduce the ecological and economic costs of species invasions. However, the difficulty of predicting which new non‐native species will establish, and where, has limited active post‐border biosurveillance efforts. Because pathways of introduction underlie spatial patterns of establishment risk, an intuitive approach is to search for new non‐native species in areas where many non‐native species have first been detected in the past. We formalize this intuition via first records distribution models (FRDMs), which apply species distribution modeling methods to the collection of first occurrence records across species (i.e. one record per species). We define FRDMs as statistical models that quantify environmental conditions associated with species' first naturalized records to predict spatial patterns of establishment risk. We model the first records of non‐native plants in the conterminous USA as a proof‐of‐concept. The novelty of FRDMs is that their inferences apply not just to the species that contributed data; they provide a rigorous framework for predicting hotspots of invasion for new non‐native taxa that share a pathway of introduction with the modeled species. FRDMs can guide survey efforts for new non‐native taxa at multiple scales and across ecosystems. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Taxon Methods Results Main Conclusions The changing frequency and intensity of climatic extremes due to climate change can have sudden and adverse impacts on the distribution of species. While species distribution modelling is a vital tool in ecological applications, current approaches fail to fully capture the distribution of climatic extremes, particularly of rare events with the most disruptive potential. Especially at the edges of species' ranges, where conditions are already less favourable, predictions might be inaccurate when these extremes are not well represented.Europe.Tree species.We present a novel approach to integrate extreme events into species distribution models based on the generalised extreme value (GEV) distribution. This distribution, following from the extreme value theory has been established as a valuable tool in analysing climatic extremes, both in an ecological context and beyond. The approach relying on the GEV distribution is broadly applicable, readily transferable across species and relies on widely available data. We demonstrate the efficacy of our approach for 28 European tree species, illustrating its superior ability to fully capture the distribution of climatic extremes compared to state‐of‐the‐art methods.We found that incorporating parameters on climatic extremes derived from the GEV distribution increased model performance (AICmodel) and characterised range edges more accurately (AUCedge) compared to competing approaches. However, general AUC values were only marginally increased across the species and study period analysed. Overall, the GEV model predicted a narrower niche for the species included in this study.Incorporating climatic extremes can impact spatial predictions of species distribution models, especially at range margins. We found that using the GEV distribution to characterise extreme variables in SDMs yields the best performance at these distribution edges. Given the importance of range edges for species conservation, a detailed inclusion of extremes in SDMs employed for those applications will help ensure robust conclusions. [ABSTRACT FROM AUTHOR]

ABSTRACT Species distribution models (SDMs) are critical to the adaptive management of fisheries under climate change. While many approaches projecting marine species range shifts have incorporated the effects of temperature on movement, there is a need to incorporate a wider suite of ecologically relevant predictors as temperature‐based SDMs can considerably under‐ or over‐estimate the rate of species responses to climate shocks. As a subarctic ecosystem at the sea ice margin, the Eastern Bering Sea (EBS) is warming faster than much of the global ocean, resulting in the rapid redistribution of key fishery and subsistence resources. To support long‐term planning and adaptation, we combine 40 years of scientific surveys with a high‐resolution oceanographic model to examine the effects of bottom temperature, oxygen, pH and a regional climate index (the extent of the EBS ‘cold pool’) on range projections through the end of the century. We use multimodel inference to partition uncertainty among earth systems models, climate scenarios and distribution model parameterizations for several ecologically and economically important EBS groundfish and crabs. Covariate choice is the primary source of uncertainty for most species, with models that account for spatial responses to the cold pool performing better and suggesting more extensive northward movements than alternative models. Models suggest declines in the probability of occurrence at low pH and oxygen concentrations for most species. We project shifts that are directionally consistent with, yet larger than those previously estimated for most species, suggesting that accounting for large‐scale climate variability in species distribution models may substantially alter range projections. [ABSTRACT FROM AUTHOR]

Climate change is projected to cause extensive plant range shifts, and, in many cases such shifts already are underway. Most long‐term studies of range shifts measure emergent changes in species distributions but not the underlying demographic patterns that shape them. To better understand species' elevational range shifts and their underlying demographic processes, we use the powerful approach of rephotography, comparing historical (1978–1982) and modern (2015–2016) photographs taken along a 1000‐m elevational gradient in the Colorado Desert of Southern California. This approach allowed us to track demographic outcomes for 4263 individual plants of 11 long‐lived, perennial species over the past ~36 years. All species showed an upward shift in mean elevation (average = 45 m), consistent with observed increasing temperature and severe drought in the region. We found that varying demographic processes underlaid these elevational shifts, with some species showing higher recruitment and some showing higher survival with increasing elevation. Species with faster life‐history rates (higher background recruitment and mortality rates) underwent larger elevational shifts. Our findings emphasize the importance of demography and life history in shaping range shift responses and future community composition, as well as the sensitivity of desert systems to climate change despite the typical “slow motion” population dynamics of perennial desert plants. [ABSTRACT FROM AUTHOR]

Radiocarbon dating of woolly mammoths remains from the Minusinsk Depression allowed us to clarify the peculiarities and timing of the species distribution in southern Siberia in the Late Pleistocene. It was demonstrated in this work that mammoths were most numerous in the cold periods in southern Siberia, and this species reached its maximal number during the Last Glacial Maximum. At the moment, there is no single discovery of a mammoth that could be confidently attributed to a warm time interval. It is possible that, during the warm intervals of the Late Pleistocene, the conditions in the south of Siberia were unfavorable for a permanent habitat of the Mammuthus primigenius species. In general, the mammoths of the Minusinsk Depression preserve species-specific stable carbon and nitrogen isotope (δ13C and δ15N) signature in the bone collagen as compared with other large herbivores. The enriched values of δ15N with the depleted δ13С were noted for them; on the contrary, reindeer demonstrate the depleted δ15N values and the enriched δ13С. The isotopic signals of other species of herbivorous mammals are located between the ranges for mammoths and reindeer. A comparison of data obtained from δ13C and δ15N for the remains of woolly mammoths from the Minusinsk Depression with similar indices in animals of the north of Eastern Siberia reveals significant differences. Differences in the diet of animals in the Minusinsk Depression and mammoths of other regions are one of the possible reasons for this phenomenon. However, similar trends (relatively depleted δ15N values and enriched δ13C values) in the Late Pleistocene are typical for both reindeer and woolly rhinoceroses of the Minusinsk Depression. This suggests that differences between the mammoth remains of the Minusinsk Depression and mammoths of the northern territories in carbon and nitrogen stable isotopes are associated not only with the type of nutrition, but also with somewhat different isotopic background of the regions caused by a local environment. [ABSTRACT FROM AUTHOR]

The faunal composition of Amphipoda crustaceans of continental water bodies in northwestern Russia is analyzed. To compile a checklist of amphipod species, data from original collections made in 1998–2021, the collections of the Zoological Institute, and published information are used. To date, 29 species of amphipods have been recorded from the continental waters of the region. An arealogical analysis of the faunal composition reveals six groups or distribution patterns: Holarctic, West Palearctic, and North Atlantic estuaries, and further three groups of emigrants (settlers) from the Baikal–Siberian, Ponto-Caspian, and Arctic regions. The greatest species richness is recorded in estuarine sections of Baltic Sea rivers on the territories of Leningrad and Kaliningrad oblasts, as well as freshwater bodies of the Republic of Karelia. In terms of species richness, estuarine species amphi-Atlantic in distribution and representatives of allochthonous elements of fauna (invasive species) from the Ponto-Caspian basin dominate in the region. The most common in the region are representatives of Holarctic and Palearctic complexes, as well as species of Arctic and Baikal–Siberian origins. Among them, the following species are most often be recorded in lakes: Gammarus lacustris, Monoporeia affinis, Palaseopsis quadrispinosa, and Gmelinoides fasciatus, compared to G. zaddachi, G. oceanicus, G. tigrinus, and Pontogammarus robustoides in estuarine brackish waters. Human-mediated introductions, both intentional and accidental, must have facilitated the appearance of invasive species in the fauna of northwestern Russia. In the future, an increase in species richness in the region can be expected to occur in two ways: through the introduction of marine species into freshwater and due to speciation. [ABSTRACT FROM AUTHOR]

Leopard seals have traditionally been considered Antarctic predators with a Southern Ocean distribution. Historically, sightings north of the Antarctic Polar Front were considered extralimital. However, recent studies suggest a significant presence of leopard seals in subantarctic regions. Here, we assess the spatial occurrence, residency status, and temporal trends of leopard seals in Chile using historical records, stranding reports, standardized monitoring data, photo-identification (photo ID) catalogs, and sightings from four research expeditions. We also characterize glaciers where sightings are concentrated, identifying glaciological and geomorphic attributes that prolong iceberg residency time, which is linked to high leopard seal concentrations. Based on these attributes, we evaluated other potential suitable glacial habitats in Patagonia. We obtained 438 sighting records of leopard seals from 1927 to 2023. Over the last 15 years, we documented a 4-18% annual increase in stranding events reported to national authorities. Most sightings (75%) were concentrated in two hotspots: National Park San Rafael Lagoon, located in Northern Patagonia, and Parry Fjord in Tierra del Fuego. Using photo ID catalogs, we identified 19 resident leopard seals, including 16 multi-year residents observed between 2010-2023 (10 in San Rafael, 6 in Tierra del Fuego) and 3 potential residents (observed multiple months in the same year in Tierra del Fuego). San Rafael monitoring data showed no inter-annual trend, but seasonal trends were observed. We also provide evidence of breeding in Chile, with records of at least 14 pups born and at least two females giving birth in multiple years. Our habitat characterization suggests that calving flux, fjord sinuosity, and fjord width variation are crucial for prolonging iceberg residency in hotspot areas. Based on these attributes, we identified 13 additional fjords in Patagonia as "very likely" suitable for leopard seals. Our study confirms that Patagonia is part of the species' breeding distribution, shifting the paradigm that leopard seals are merely visitors north of the Antarctic Polar Front. Given the limited number of suitable glaciers in Chile and the potential impacts of climate change, our assessment highlights glacial retreat as a major threat for the ecosystem of this pagophilic marine apex predator in South America. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) are often generated to inform conservation plans. When developed for use in spatially-restricted areas, such as protected areas, investigators often make arbitrary decisions as to the geographic extent from which locality data to inform the model are drawn (i.e. the "study extent" of the model). However, there has been little attention to the impacts of this decision on model predictions. Here we explore the impacts of study extent on SDM predictions of (i) suitable habitat for or (ii) the actual occurrence of individual species, as well as on (iii) the identification of sites that could support multiple species (i.e. from stacked-SDMs). Focusing on six amphibian species of conservation concern at the edge of their range in western Canada, we generated SDMs using range-wide, ecoregion, and political study extents and compared the alternative predictions for each species in one of two national parks of interest. Differences in model predictions were substantial, with precent agreement among models developed with different extents as low as 10% for one of the species. Study extent also influenced the ability of models to predict independent occurrence at the edge of the range, although most models performed poorly in this regard (AUC < 0.7). Finally, study extent influenced stacked predictions, suggesting that uncertainty in individual species predictions muddies interpretation of SDMs at the community-level. Importantly, results varied across species and region, precluding simple recommendations for choosing a study extent; Instead, uncertainty arising from this decision should be quantified before using SDMs in conservation planning. [ABSTRACT FROM AUTHOR]

The tropical Andes region harbors areas that are highly significant for biodiversity at both global and local scales. However, despite the severe conservation threats that this region has to confront, conservation initiatives are limited, by funding and because of the need for more information to decide which areas are priorities for conservation. Identifying Important Plant Areas (IPAs) offers a valuable methodology for establishing conservation priorities, a particularly complex task in a mega-biodiverse region such as the northern Andean tropics. Due to its iconic recognition and conservation value, this study focused on the Espeletiinae subtribe (Asteraceae) as a model group; hence, the distribution data for 138 species was compiled from 5560 georeferenced records. Using the IPA methodology, we divided the study area, this is, the distribution area of the subtribe in the Andean tropics, into 220 Units of Analysis (UA) represented by 10 × 10 km plots. Refined species' distribution areas, incorporating richness, threatened species, and ecosystem-based richness distributions, were analyzed using newly generated maps to evaluate the conservation value of each UA. Our analysis identified 176 UAs with some level of relevance using sub-criterion cA1 (with 59 species) and 51 UAs using sub-criterion cB (with 76 species). Integrating both criteria, we classified 11 UAs as high-priority, 62 as medium-priority, and 147 as low-priority, highlighting the IPAs that require focused conservation efforts. Two identified high-priority IPAs are located in Venezuela and nine in Colombia, predominantly associated with the Eastern Cordillera. These areas concentrate between 7 and 12 species. They are mainly linked to the páramo complexes of Colombia and the Sierra Nevada in Venezuela, primarily within Cool Temperate Moist Grassland ecosystems on mountains. Our results provide a spatial planning procedure and analytical tool for decision-makers to guide conservation management and actions across northern Andes. [ABSTRACT FROM AUTHOR]

Transferability of species distribution models (SDMs) is vital for guiding biological conversation in the changing marine ecosystems, whereas most SDMs have remained insufficiently tested in terms of transferences. Particularly, the roles of biotic interactions in shaping ecological niches had less been considered when predictive models are transferred into a new circumstance. Therefore, using silver croaker (Pennahia argentata) and slender lizardfish (Saurida elongata), two keystone predators in the coastal systems as examples, this study examined how the consideration of abiotic and biotic factors as well as spatial autocorrelation would improve the transferability of prevalent SDMs. We collected the data of species abundance and hydrological variables from coastal waters of Shandong Peninsula, China, and developed a framework to evaluate the interpolation performance and spatial transferability of SDMs with respect to different modelling algorithms and combinations of covariates. The covariates tested included (1) abiotic environmental variables only; (2) biotic variables of prey availability only; (3) both abiotic and biotic variables; and (4) spatial autocorrelation in addition to other variables. Generally, our results showed that including abiotic and biotic variables simultaneously could improve the model transferability, whereas biotic models exhibited greater uncertainty and overestimation in spatial transferences when delineating suitable habitats. Besides, models accounting for spatial autocorrelation yielded more accurate forecasts for slender lizardfish's abundance, and were less limited by geographic distance in transference. Regarding the model algorithms, GLM slightly outperformed GAM and RF overall, while RF showed more robust spatial extrapolations in many cases. Our transferability evaluations offer the opportunity to extend the use of biotic signals and spatial autocorrelation to improve the forecasts of habitat suitability, which would be informative for guiding marine conservation actions. [ABSTRACT FROM AUTHOR]

Practices increasing agrobiodiversity and ecological services are the first step toward an agroecological approach to organic greenhouse production. In this study, we compared innovative, diversified, and less intensive greenhouse systems (INNs) with business as usual (BAU) at three European sites (Belgium, Switzerland, and Italy). We evaluated the management effects on weed community composition, diversity, and traits distribution. In comparison with BAU, the INNs had higher weed density (up to +663%) in the three sites, over the entire rotation, higher species richness in Belgium, and lower community evenness in Italy and Switzerland. We observed changes in the distribution of traits between INN and BAU systems at the three sites, but without a clear pattern. Changes in the functional profiles were observed even though the communities were characterized by few and dominant species. The results showed a shift in weed communities between the systems in terms of weed species distribution and functional traits. Despite this, the INN systems did not exhibit a clear trend toward promoting more service-oriented communities compared to the BAU systems. [ABSTRACT FROM AUTHOR]

ABSTRACT Common horsetail (Equisetum arvense L., syn.: field horsetail) holds a long tradition in the supportive treatment of numerous diseases. A frequently observed problem is the risk of confusing Equisetum arvense plants with another closely related species Equisetum palustre (syn.: marsh horsetail) due to its morphological similarities. The distinction between the two species during collection/harvest is further complicated by the fact that both species share similar habitats. This, however, is of particular importance because E. palustre contains toxic alkaloids (palustrine and palustridiene) while this is not the case for E. arvense used for medicinal purposes (Equiseti herba). The aim of this study was the classification of horsetails using near infrared spectroscopy (NIR). Therefore, over 370 E. arvense and E. palustre samples originating from all over Germany, consisting of 2 years of harvest, were analysed using two different devices from different manufacturers: (a) a miniature (portable) NIR device and (b) a benchtop NIR device. Initial unsupervised machine learning techniques (PCA and t‐SNE) provided insightful visualizations for the distribution of both species within the data space. After applying variable screening to the spectral data, a variety of supervised machine learning models based on different algorithms were trained to predict the species from an individual spectrum. In a repeated cross‐validation (CV) approach, it could be shown that the spectra from both spectrometers are sufficient to achieve classification accuracies around 90%. Additionally, the data allowed for discriminating between harvesting seasons as well. The success of the complete workflow is further emphasized by assessing its reliability through posterior probabilities, which were high for the predicted class labels, implying a satisfying model certainty. [ABSTRACT FROM AUTHOR]

Summary Juniperus spp. are keystone shrubs in western North America and important climatic indicators in paleo‐records. However, a lack of taxonomic resolution among fossil species limits our ability to track past environmental changes. Plant macrofossils at Rancho La Brea (RLB) allow for reconstructions of juniper occurrence to species across 60 000 yr. We use microscopy, image analysis, species distribution modeling (SDM), and radiocarbon dating to identify an unknown Juniperus species at RLB and put it into chronological context with fossil Juniperus californica at the site to infer past environmental conditions. We identify the unknown taxon as Juniperus scopulorum Sargent, 1897. The Pleistocene occurrence of this species in California expands its known distribution and documents its extirpation. Temporal ranges of the two fossil junipers alternate, revealing a pattern of differential climatic sensitivity throughout the end of the Pleistocene. Occurrence patterns suggest sensitivity to temperature, moisture availability, and the presence of two mega‐droughts at c. 48–44.5 ka and c. 29.3–25.2 ka. Extirpation of both taxa by c. 13 ka is likely driven by climate, megafaunal extinction, and increasing fire. The extirpation of fossil junipers during these past climatic events demonstrates vulnerability of juniper species in the face of global change. [ABSTRACT FROM AUTHOR]

In this study, pyrite flotation in seawater in the presence of Cu2+and Pb2+ and the underlying mechanisms were investigated systematically. Flotation results indicated that Cu2+ and Pb2+ increased pyrite recovery from 52.51% to 79.45% and 72.57% in weak alkaline seawater (pH 8) due to the increased surface hydrophobicity. Solution species distribution and electrochemical studies cross-confirmed that the Cu2S and Pb(OH)2 layer formed on the pyrite surface at pH 8, subsequently increasing the adsorption sites of xanthate on the pyrite surface. Differently, the pyrite flotation remained at a lower recovery of around 20% than that with the addition of 10−7–10−5 M Cu2+ and Pb2+ in strong alkaline seawater (pH 10). No activation species were adsorbed on the pyrite surface at pH 10 due to the coverage of hydrophilic precipitation on the pyrite surface, resulting in a poor floatability. This study therefore provides scientific guidelines for pyrite separation in seawater in the presence of Cu2+ and Pb2+. [ABSTRACT FROM AUTHOR]

All populations are affected by multiple environmental drivers, including climatic drivers such as temperature or precipitation and biotic drivers such as herbivory or mutualisms. The relative response of a population to each driver is critical to prioritizing threat mitigation for conservation and to understanding whether climatic or biotic drivers most strongly affect fitness. However, the importance of different drivers can vary dramatically across species and across populations of the same species. Theory suggests that the response to climatic versus biotic drivers can be affected by both the species' fundamental niche breadth and the latitude of the population at which the response is measured. However, we have few tests of how these two factors affect relative response to drivers separately, let alone tests of how niche breadth and latitude together influence responses. Here, we use a meta‐analysis of published studies on population response to climatic and biotic drivers in terrestrial plants, combined with estimates of climatic niche breadth and position within climatic niche derived from herbarium records, to show that species' niche breadth is the primary determinant of response to climatic versus biotic drivers. Namely, we find that response to climatic drivers changes only minimally with increasing niche breadth, while response to biotic drivers increases with niche breadth. We see similar relationships when considering range size instead of niche breadth. Surprisingly, we find no effects of latitude on the relative effect of climatic versus biotic drivers. Our work suggests that populations of species with small and large ranges experience similar extirpation risks due to the negative impacts of climate change. By contrast, populations of species with large (but not small) ranges may be highly susceptible to changes in densities or distributions of interacting species. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate change poses a significant threat to marine ecosystems, potentially altering the distribution of marine organisms and causing many species to migrate towards the poles. The habitat changes of species targeted for fishing are likely to affect fishing activities and the livelihoods of coastal communities. Hence, the present study analyzed the distribution of Indo‐Pacific king mackerel (IKM) in the Taiwan Strait (TS) by using ensemble modeling and considering two representative concentration pathway (RCP) scenarios (2.6 and 8.5) to assess the implications of predicted climate change. Four species distribution models incorporating sea surface height, chlorophyll, salinity, and temperature were used as inputs to create an ensemble model that replicated IKM distribution under current ocean conditions. The ensemble habitat model does not show monotonic decrease of IKM habitat but reveals more complex change in the 21st century with a hump around 2050. By end of the century, IKM is predicted to decline under RCP 8.5 scenario more seriously than under RCP 2.6. The study highlights the need for adaptation measures in managing IKM fisheries in the TS, emphasizing the importance of considering non‐unidirectional habitat changes in the global oceans as well. [ABSTRACT FROM AUTHOR]

Understanding the factors affecting species distributions is a central topic in ecology and biogeography. However, most research on this topic has focused on species inhabiting terrestrial environments. At broad scales, abiotic variables consistently serve as primary determinants of species' distributions. In this study, we investigated the explanatory power of different abiotic variables in determining the distribution patterns of sea snakes on a global scale. Additionally, as the boundaries of realized thermal niches have significant implications for the ecology of species and their geographic distributions, we evaluated the asymmetry of realized thermal limits (i.e., differences in variances between the upper and lower limits of the realized thermal niche). We obtained 10 marine environmental variables from global databases along with >5000 occurrence records for 51 sea snake species in 4 genera across the group's entire known geographic range. Using these data, we employed correlative ecological niche modeling to analyze the influence of the individual variables in explaining species' distributions. To estimate the realized thermal limits of each species, we extracted the mean, minimum, and maximum temperature values at four depths (superficial, mean benthic, minimum benthic, and maximum benthic) for each occurrence record of the species. We then evaluated the asymmetry of the realized thermal niche by measuring and comparing the variances in the upper and lower limits. Both analyses (the importance of variables and realized thermal limit asymmetry) were performed at three taxonomic levels (sea snakes as a lineage of marine-adapted elapids [true sea snakes + sea kraits], subfamily, and genus) and two spatial resolutions. Overall, we found that temperature, silicate, nitrate, salinity, and phosphate concentrations were the most influential factors in explaining the spatial distribution patterns of sea snakes, regardless of taxonomic level or spatial resolution. Similarly, we observed that the realized thermal limits were asymmetric, with a higher variance in the lower limits, and that asymmetry decreased as the taxonomic level and spatial resolution increased. [ABSTRACT FROM AUTHOR]

Background: Microgenderome or arguably more accurately microsexome refers to studies on sexual dimorphism of human microbiomes aimed at investigating bidirectional interactions between human microbiomes, sex hormones, and immune systems. It is important because of its implications to disease susceptibility and therapy, in which men and women demonstrate divergence in many diseases especially autoimmune diseases. In a previous report [1], we presented analyses of several key ecological aspects of microgenderome by leveraging the large datasets of the HMP (human microbiome project) but failed to offer species-level composition differences such as sexually unique species (US) and enriched species (ES). Existing approaches, for such tasks, including differential species relative abundance analysis and differential network analysis, possess certain limitations given that virtually all rely on species abundance alone or are univariate, while ignoring species distribution information across samples. Obviously, it is both species abundance and distribution that shape/drive the structure and dynamics of human microbiomes, and both should be equally responsible for the universal heterogeneity of microbiomes including the sexual dimorphism. Results: Here, we fill the gap by taking advantages of a recently developed computational algorithm, species specificity, and specificity diversity (SSD) framework (refer to the companion article) to reanalyze the HMP and complementary seminovaginal microbiome datasets. The SSD framework can randomly search and catalogue the sexually specific unique/enriched species with statistical rigor, guided by species specificity (a synthetic metric of abundance and distribution) and specificity diversity (SD). The SSD framework reveals that men seem to have more unique species than women in their gut and reproductive system microbiomes, but women seem to have more unique species than men in the airway, oral, and skin microbiomes, which is likely due to sexual dimorphism in the hormone and immune systems. We further investigate co-dependency and heterogeneity of those sexually unique/enriched species across 15 body sites, with core/periphery network analyses. Conclusions: This study not only produced sexually unique/enriched species in the human microbiomes and analyzed their codependency and heterogeneity but also further validated the robustness of the SSD framework presented in the companion article, by performing all negative control tests based on the HMP gut microbiome samples. [ABSTRACT FROM AUTHOR]

Background: Differentiating the microbiome changes associated with diseases is challenging but critically important. Majority of existing efforts have been focused on a community level, but the discerning power of community or holistic metrics such as diversity analysis seems limited. This prompts many researchers to believe that the promise should be downward to species or even strain level—effectively and efficiently identifying unique or enriched species in diseased microbiomes with statistical rigor. Nevertheless, virtually, all species-level approaches such as differential abundance and differential network analysis methods exclusively rely on species abundances without considering species distribution information, while it can be said that distribution is equally, if not more, important than abundance in shaping the spatiotemporal heterogeneity of community compositions. Results: Here, we fill the gap by developing a novel framework—species specificity and specificity diversity (SSD)—that synthesizes both abundance and distribution information to differentiate microbiomes, at both species and community scales, under different environmental gradients such as the healthy and diseased treatments. The proposed SSD framework consists of three essential elements. The first is species specificity (SS), a concept that reincarnates the traditional specialist-generalist continuum and is defined by Mariadassou et al. (Ecol Lett 18:974-82, 2015). The SS synthesizes a species' local prevalence (distribution) and global abundance information and attaches specificity measure to each species in a specific habitat (e.g., healthy or diseased treatment). The second element is a new concept to introduce here, the (species) specificity diversity (SD), which is inspired by traditional species (abundance) diversity in community ecology and measures the diversity of specificity (a proxy for metacommunity heterogeneity, essentially) with Renyi's entropy. The third element is a pair of statistical tests based on the principle of permutation tests. Conclusions: The SSD framework can (i) identify and catalogue lists of unique species (US), significantly enriched species (ES) in each treatment based on SS and specificity permutation (SP) test and (ii) measure the holistic differences between assemblages (or treatments) based on SD and specificity diversity permutation (SDP) test. Both capacities can be enabling technologies for general comparative microbiome research including risk assessment, diagnosis, and treatment of microbiome-associated diseases. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Methods Results Main Conclusions Historical bird atlases provide comprehensive datasets for investigating long‐term changes in species' distribution. In the context of accelerating biodiversity loss, these datasets can lend critical insights into the state of bird distributions across broad spatio‐temporal scales and provide much‐needed information for impactful conservation. In Africa, the potential of atlas data to understand changes in avian populations remains largely untapped.This study mapped changes in national distribution patterns of 1088 bird species found in Kenya.Tapping into one of the earliest atlas databases, this study compared Kenyan bird atlas data collected between 1970 and 1984 with recent citizen science data sourced from the Kenya Bird Map project and eBird to determine changes in ranges across 50 years. We produced maps displaying, for every 27 × 27 km square of the country, whether a species appeared, was present throughout both periods, or disappeared. We account for the change in data collection effort between the two periods by quantifying the confidence of the change for each square.The maps produced for each species are publicly accessible through an interactive website: https://kenyabirdtrends.co.ke/. We found that related species tended to experience similar changes in their distribution ranges. The ranges of Palearctic migrants and scavengers declined drastically, while introduced birds experienced a significant range increase over the past 50 years.This study demonstrates the potential of integrating recent citizen science data with historical atlas data to draw out the changes in range for all species at national level. The range contraction of Palearctic migrants and scavengers echoed corresponding drops in abundance at local, regional and global scales. These findings lend additional weight to the need for an increased conservation focus on migratory and scavenging birds in Kenya. [ABSTRACT FROM AUTHOR]

Invasive alien species can have severe impacts on biodiversity, economies, and well‐being and their long‐term management can involve massive costs. There is an increasing policy imperative to determine whether the management of biological invasions is effective, particularly at biological invasion fronts, but this can often be difficult to determine without extensive data collection. Furthermore, risk assessment frameworks are often used to guide decision‐making and management, but these can be hampered by a lack of information about the extent and dynamics of a biological invasion following an introduction within a new region. Incorporating information on the dynamics of biological invasions into these frameworks could provide useful information for decision‐makers including a baseline for evaluating ongoing management approaches. Here, we outline a generalisable mechanistic species distribution modelling framework that is informed by patterns of spread observed in other invaded regions and can provide a relatively rapid assessment of the likely spatial and temporal dynamics of a biological invasion in the absence of interventions. To demonstrate this approach, we consider the effectiveness of rapid eradications carried out in four European countries to prevent the spread of the yellow‐legged hornet (Vespa velutina nigrithorax) following the implementation of Regulation (EU) 1143/2014 on invasive alien species. Synthesis and applications. By predicting the extent of a biological invasion in the absence of timely interventions and comparing this to the current distribution of the yellow‐legged hornet, we found that management measures implemented in these countries appear to have been effective in limiting the spread of the species in Europe. Additionally, the model framework may be useful to inform the identification of high‐risk areas for surveillance measures to be prioritised in view of rapid detection and early eradication activities. [ABSTRACT FROM AUTHOR]

Aim Location Methods Results Main Conclusions Rapid loss in global insect diversity has generated substantial public worry due to their critical ecological roles. However, there is controversy about the effectiveness of the global‐scale hotspots in guiding the conservation of diversity at the regional scale. Even worse, little is known about the knowledge of insect distributional dynamics in many understudied regions, such as East and Southeast Asia. Here, to guide for setting regional‐scale conservation priorities for insect diversity, we explore hawkmoths (Lepidoptera: Sphingidae) for their distributional dynamics and identify regional hotspots requiring protection.South China (including Guangdong, Guangxi, Hainan, Hong Kong and Macau) and northern Vietnam (17°~26.5° N, 102°~117.5° E).Species distribution models were generated for 194 hawkmoth species based on 3597 occurrence records to predict their distributions. We calculated the spatial patterns of taxonomic and phylogenetic diversity and identified regional hotspots. Furthermore, the potential assembly mechanisms underlying insect diversity were explored by analysing the rates of speciation, extinction and dispersal between phyloregions.(a) The coastal regions of South China and northern Vietnam represent a regional hotspot of hawkmoths in East and Southeast Asia, with significantly higher α‐diversity than that in inland regions. (b) Dispersal played a more important role than local speciation and extinction in the formation of regional hawkmoth hotspots.In this study, the ‘Out‐of‐the‐tropics model’ can explain the formation of the hawkmoth regional hotspots and the enhanced version of the ‘Pure dispersal model’ can explain the formation of the hotspots in Hainan Island. Compared with the local speciation and extinction, dispersal is the main driving factor that promoted the formation of the regional biodiversity hotspot of hawkmoths in South China. The case of Hainan Island suggests that protection within hotspots needs to account for specific regional macro‐evolutionary dynamics rather than indiscriminate coverage of identified hotspots. [ABSTRACT FROM AUTHOR]

ABSTRACT Background Aims Materials and Methods Results Discussion Conclusion The study of island species richness has gone far beyond traditional theories, as more and more studies attempt to include new predictor variables besides island area. Despite the rich bat diversity of Mediterranean islands, no studies have examined the factors influencing chiropteran species richness in such a geographic context.We used Greek islands as a model to detect drivers of bat species richness based on a broad species occurrence dataset from islands of the Aegean and Ionian Seas, which was explored using 10 potential predictor variables.Initially, we comprehensively evaluated all available data and sources for 53 Greek islands, deemed essential. This resulted in a reduced set of 28 islands. Predictors were grouped into three categories: island area, landscape diversity and island isolation. Generalised linear models were employed to identify the most significant factors explaining bat species richness in the 28 islands.Tree cover and the distance between the islands and their nearest coast (mainland or island) best performed to predict bat species richness on Greek islands.We show the important role of landscape composition and degree of isolation in influencing the distribution of bat species on islands.We highlight the importance of forest habitats and the vital role of their management and protection, especially in the insular systems of the Mediterranean basin, where the risk of forest degradation or loss due to wildfires and land use change is especially high. [ABSTRACT FROM AUTHOR]

Over 20 years ago, ecologists were introduced to the site occupancy model (SOM) for estimating occupancy rates from detection‐nondetection data. In the ensuing decades, the SOM and its hierarchical modeling extensions have become mainstays of quantitative ecology, and estimating occupancy rates has become one of the most common applications of ecological field data. Here, we review 364 peer‐reviewed articles published between 2019–2021 that estimated occupancy. We first document broad patterns in study design and statistical methods to provide educators, developers of methodology and software, and ecologists with a clear picture of the landscape of methodologies used to estimate animal occupancy. Second, we conduct a focused review of a subset of 98 papers that applied the hierarchical SOM, drawing from methodological literature to identify discrepancies between SOM applications and methodological best practices. We discuss limits to statistical power, issues with model checking and model selection procedures, potential problems arising from unmodeled non‐independence, and reproducibility. We highlight areas of rapid advancement in interpreting animal occupancy related to animal movement, imperfect detection, and the occupancy–density relationship. We aim to help readers understand the landscape of methods available, motivate shifts toward robust and reproducible science, and inspire new software and methodological research. [ABSTRACT FROM AUTHOR]

Species distribution models are key to evaluate how climate change threatens European forests and tree species distributions. However, current models struggle to integrate ecophysiological processes. Mechanistic models are complex and have high parameter requirements. Some correlative species distribution models have tried to include traits but so far have struggled to directly connect to ecophysiological processes. Here, we propose a new strategy in which species distributions are based on safety margins which represent species' proximity to their physiological thresholds. We derived frost and drought safety margins for 38 European tree species as the difference between physiological tolerance traits and local maximum stress. We used LT50 and Ψ50 as tolerance traits for frost and drought, respectively, and local minimum temperature and minimum soil water potential as maximum stress. We integrated these safety margins into a species distribution model, which tests if the probability of species presence declines rapidly when the safety margin reaches zero, when physiological stress exceeds the species' tolerance traits. Our results showed thaet 35 of the 38 studied species had their distribution explained by one or both safety margins. We demonstrated that safety‐margins‐based model can be efficiently transferred to species for which occurrence data are not available. The probability of presence dropped dramatically when the frost safety margin reached zero, whereas it was less sensitive to the drought safety margin. This differential sensitivity may be due to the more complex regulation of drought stress, especially as water is a shared resource, whereas frost is not. Our analysis provides a new approach to link species distributions to their physiological limits and shows that, in Europe, frost and drought safety margins are important determinants of species distributions. [ABSTRACT FROM AUTHOR]

Macrocybe is a well-studied genus in the family Callistosporiaceae (Basidiomycota). Currently, the genus comprises eight species with worldwide distribution. All species in this genus are relatively large compared to other edible mushrooms and are commonly consumed by locals. Cultivation methodologies have been developed for several species of the genus, including M. gigantea , M. crassa , M. titans , and M. lobayensis. These mushrooms can be cultivated in lignocellulosic wastes such as sawdust, straw, and other agro-industrial wastes. The nutritional compositions have been identified for M. gigantea , M. crassa , and M. lobayensis , revealing that they are rich in fibers, proteins, and various vitamins. Although these mushrooms are of culinary significance, precautions should be taken when consuming them due to their potential cyanic toxicity. In addition to being rich in different nutrients, Macrocybe species possess medicinal properties such as antimicrobial, antioxidant, immunomodulatory, anticancer, anti-inflammatory, hepatoprotective, and several other beneficial effects. Several species are commercially available in countries like China and Thailand, and the commercial potential is high due to the large size, taste, and long shelf life of these mushrooms. There is significant potential for cultivating species of this genus and introducing their artificial cultivation practices to various counties worldwide. Diverse value-added products can also be produced using Macrocybe species. [ABSTRACT FROM AUTHOR]

Background: Understanding the patterns and processes of species distributions has long remained a central focus of biogeographical and ecological research. While the evidence for elevational patterns in species richness is widespread, our understanding of underlying causes and mechanisms remains limited. Therefore, this study aimed to entangle the influence of environmental variables on plant species richness along elevational gradients in the Western Himalayas. Methods: We compiled elevational distribution for about 1150 vascular plants using the published literature and available database. The species richness was estimated in 100-m elevational bands using the range interpolation method. We used the generalised linear model and structural equation modelling (SEM) framework to identify the direct and indirect effects of climatic factors on species richness. Results: Our results indicated that primary environmental correlates of species richness varied with elevational gradients. Climatic variables combined with energy and water availability were more important than the topographic heterogeneity. Further, the direct and interaction effects of climatic variables were more substantial than their indirect effects. The indirect effects of climate are more strongly mediated by water–energy dynamics than the energy alone. Conclusions: Overall, our findings emphasise the importance of considering direct effects and interactions among environmental variables while studying the underlying mechanisms governing elevational biodiversity gradients. Species richness appeared to be shaped by climatic tolerances rather than habitat heterogeneity at regional scales. This information can have implications for biodiversity dynamics under environmental change. [ABSTRACT FROM AUTHOR]

Introduction: Global climate change and associated stressors threaten forest ecosystems due to the rapid pace of climate change, which could exceed the natural migration rate of some tree species. In response, there is growing interest to research and implement forest assisted migration (FAM). Here, we used a species-independent indicator based on climate analogy, according to the sigma (dis)similarity (σd) index, to match planting sites across the eastern US with (future) climatically-compatible seedlots (CCS). Methods: We developed CCS for a grid composed of 1 × 1° of latitude and longitude. CCS were based on future climate analogs with ≤2σd analogy to ensure CCS were representative of future climate change. CCS were located for three time periods, 2030's, 2050's, and 2090's and three emissions scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) from the Coupled Model Intercomparison Project phase 6 database, using 12 climate variables. Results: CCS were identified for the majority of 1 × 1° grids based on the SSP3-7.0 scenario. Approximately 28% of 1 × 1° grid's 2090's projections included future climate novelty. The 2030's, 2050's, and 2090's CCS were located on average 222, 358, and 662 km or 1, 2, and 3 eastern seed zones away from the 1 × 1° grids, respectively. CCS were also located further south-southwest (188–197°). In addition, the average forest cover of CCS was approximately 2%, 5%, and 10% less than that of the 1 × 1° grids. Discussion: Our development and synthesis of CCS emphasized four key results: (i) average distances to 2030's and 2050's CCS were similar to seed-transfer guidelines for some tree species, but 2090's CCS exceeded current recommendations; (ii) south-southwesterly locations of CCS aligned with tree species habitat distribution dynamics; (iii) future climate novelty potentially challenges the conceptual basis of FAM if tree species are not adapted to climate change; and (iv) variation in forest cover among CCS presents potential opportunities and challenges due the presence or absence of forestland to source seed. Ultimately, our goal was to locate and synthesize CCS that could enable FAM decision support. [ABSTRACT FROM AUTHOR]

Accurate knowledge of species distributions is foundational for effective conservation efforts. Bats are a diverse group of mammals, with important roles in ecosystem functioning. However, our understanding of bats and their ecological importance is hindered by poorly defined ranges, mostly as a result of under-recording. This issue is exacerbated in Africa by the ongoing rapid discovery of new species, both de novo and splits of existing species, and by inaccessibility to museum specimens that are mostly hosted outside of the continent. Here we present the African bat database – a curated set of 17,285 unique locality records of all 266 species of bats from sub-Saharan Africa, vouched for by specimens and/or genetic sequencing, and aligned with current taxonomy. Based on these records, we also present Maxent-based distribution models and calculate the IUCN Red List metrics for Extent of Occurrence and Area of Occupancy. This database and online visualization tool provide an important open-source resource and is expected to significantly advance studies in ecology, and aid in bat conservation. [ABSTRACT FROM AUTHOR]

Anthrax outbreaks caused by the soil‐borne bacterium Bacillus anthracis have been known to occur often in Africa, impacting both wildlife and livestock and occasionally infecting humans. Modelling the current distribution and predicting suitable habitats for this bacteria species is therefore critical for supporting effective planning and control measures for anthrax outbreaks. Despite its impact, the knowledge on the ecology of this pathogen is still limited. This can be due to intricate interactions between anthropogenic and environmental factors and the variety of species it affects. Therefore, detailed, site‐specific analyses are essential for contributing to the understanding of the ecology of anthrax. This study used the maximum entropy modelling algorithm (MaxEnt) method to predict suitable habitat and environmental conditions that may support anthrax distribution and spore survival in Tarangire National Park, in Tanzania. Model inputs included 14 predictors from World Climatic, Landsat satellite, and World Soil Information datasets, as well as 636 presence‐only occurrence data from park records from 2013 to 2023. The predicted suitable area favouring anthrax spores encompassed most of the savannah and open grassland in the northern part of the park, as well as narrow patches in the park's central region. The mean test AUC score was 0.91, and the predicted probability was 0.98 for anthrax presence. On average, the predicted probability of suitable conditions substantially improved with increasing levels of extractable phosphorus, exchangeable potassium, mean annual temperature, and soil pH. Furthermore, the probability of suitable habitat was highest at lower levels of fire frequency, exchangeable sodium, and extractable aluminium. The extensive track record of anthrax outbreaks in the area may be explained by the presence of these favourable soil characteristics and climate, which point to the long‐term occurrence of anthrax spores in the park. However, the existence of suitable habitat in the northern part of the park presents opportunities for mobilising resources to mitigate the situation through activities such as targeted disease surveillance and the use of controlled fire. [ABSTRACT FROM AUTHOR]

The European pilchard (Sardina pilchardus), also known as sardine, is one of the important small pelagic species in terms of biomass and commercial interest in its areas of occurrence. In Northwest Africa, little is known about this species regarding its status and biology. However, for effective management of this resource, it is vital to understand its distribution and parameters that may influence its catch rate. The present study aims to standardize the catch per unit effort (CPUE) for the European pilchard and examine the influence of environmental factors on the catch rate distribution of sardines in Northwest African waters. This information would be analyzed based on various data schemes provided by the Fishery Committee for the Eastern Central Atlantic (FAO-CECAF). Generalized Additive Model (GAM) and Generalized Linear Model (GLM) were developed for this analysis. GAM was used to determine which environmental variable had the greatest effect on the distribution of European sardines, while GLM was used for the CPUE standardization of European sardines. The results suggest that Catch, Sea surface temperature (SST), Coastal upwelling index (CUI) and Chlorophyll-a Concentration (Chl) were the variables with high influence on the distribution of European pilchard. The standardised CPUE results by GLM showed distinct CPUE peaks around 2000, 2006, and 2013–2014. The most recent years (after 2015) show lower CPUE values than the earlier periods, suggesting potential changes in fishing efforts. The study showed the effect of ecological, environmental factors resulting from climate change on sardine population information. [ABSTRACT FROM AUTHOR]

Reintroductions are increasingly being used as a conservation tool to restore species to areas where they once existed. Unfortunately, many reintroduction projects fail to establish viable populations. Climate suitability at release sites is thought to be important in determining reintroduction outcomes, and future climate change is an essential consideration for effective reintroduction planning. Climate change threatens species in a variety of ways, such as by impacting life history traits or causing spatial and temporal distribution mismatches of interdependent species. Hibernating species, such as the hazel dormouse (Muscardinus avellanarius), may be particularly susceptible to changes in climate. For example, milder winters may increase the number of interbout arousals during hibernation, which are energetically costly. Timing of food availability may also be impacted by changing climates, potentially causing mismatches between activity and feeding opportunities. Here, we use species distribution models (SDMs) to map climate suitability for dormice in the UK. We also investigate the impact of climate suitability on a long‐running dormouse reintroduction programme, providing the first such investigation for a reintroduced mammal. We find that higher levels of current climate suitability increase the probability of reintroduction success. We find no effect of climate suitability on adult dormouse counts at reintroduction sites, but dormouse counts decline with time since reintroduction. Future projections predict that climate change may lead to more widespread climate suitability for dormice in the UK, reflecting predicted changes in seasonality, winter temperature and precipitation. Our work demonstrates the importance of understanding changing climate suitability for reintroduction planning, with potential widespread applications of SDMs for conservation projects of low‐dispersing mammals. [ABSTRACT FROM AUTHOR]

The introduction of exotic species poses one of the greatest threats to biodiversity globally. Water hyacinth is a dangerous invasive species that has harmed Ethiopia's wetland ecology and economy. This research aims to evaluate the current distribution of water hyacinth and the impact of environmental variables on its spread, while also mapping future habitat suitability under climate change scenarios and assessing how these changes may influence the species' potential expansion. To estimate the risks of climate change to the species, a predictive model was developed from six modeling methodologies to investigate the climatic suitability of target species for the years 2050 and 2070 under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP 8.5). Under the current climatic scenario, only 69.78% (789 503.8 km2) and 16.02% (181 262.8 km2) of the country is moderately and highly suitable for species dispersion and invasion respectively. The remaining 14.2% (160 620.9 km2) is unsuitable for the distribution and invasion of the species. In 2050, under the RCP4.5 and RCP 8.5, the 'highly suitable' range of water hyacinth is anticipated to expand by 16.35% and 15.39%, whereas the 'moderately suitable' area is predicted to increase by 70.81% and 71.52%, respectively. Under the RCP8.5 scenarios, compared to the current climatic conditions, in 2070 the 'highly suitable' region for the species is expected to increase by 11.48%. Its continuing growth would exacerbate the issue of ecological and economic crisis, cause significant economic and environmental harm and endanger the community's way of life. In order to avert or reduce these effects, a thorough examination of water hyacinth along the two RCPs by water resource scientists and mamangers, that takes into account how climate change is affecting water hyacinth growing locations in Ethiopia, and provides a proper solution, is mandatory. [ABSTRACT FROM AUTHOR]

Over the last century, a significant decline in the population size of the Nubian Capra nubiana has been observed across its distribution range. This decline is attributed to the changes in natural resources, including water and foraging site capacity, due to the ongoing climate change. We applied species distribution models (SDMs) to investigate the response of C. nubiana to projected climate change in the next decades. We fitted ensemble SDMs with recently developed climate data based on climate models and two different dispersal scenarios to minimize the uncertainty and bias in our SDMs prediction. Our SDMs predicted a significant shrinkage of the distribution range of the C. nubiana in the coming decades, where C. nubiana may lose ca. 60% of its area of occupancy before 2050, while it may become extinct (lose > 90% of its projected area) before the end of the current century. Our results call for urgent conservation intervention at global and national scales to halt the impact of climate change on one of the remaining top mountain ungulate species in desert ecosystems. [ABSTRACT FROM AUTHOR]

As many new evolutionary lineages are being discovered and formally named, sequencing topotypes when holotypes are not available becomes essential for taxonomy. This study uses a DNA-taxonomy approach to sequence new populations of the Ischnocnema verrucosa species complex (Brazilian Wart Frogs) from different locations, including, for the first time, individuals from the type localities. Phylogenetic analysis of the mitochondrial 16S gene recovered a monophyletic Ischnocnema verrucosa species series composed of three main clades. The most recent common ancestor was estimated to be 33.76 million years ago, and diversification within the three main clades occurred primarily during the Miocene. We delimited eight species-level lineages with high levels of sequence divergence (7% to 16%). Our study highlights the importance of DNA taxonomy and the necessity of protecting and sequencing topotypes in taxonomic studies. Our study also contributes to the conservation and understanding of the genus Ischnocnema and the biodiversity of the Brazilian Atlantic Forest region. [ABSTRACT FROM AUTHOR]

The spiders in the genus Pardosa C.L. Koch, 1847, are a young lineage of the family Lycosidae Sundevall, 1833, that exhibit high species diversity and widespread distribution. Pardosa is abundant in open and disturbed environments. In fact, most of its species live in grasslands, and the few that live in forests switched habitats relatively recently. The genus markedly prefers grasslands with a broad range of climates. Thus, its origin and diversification were probably associated with grassland expansions during the late Cenozoic. To test this hypothesis, we developed a global phylogenetic hypothesis that helps reconstruct the biogeographic patterns of the genus Pardosa using three nuclear (18S, ITS2, and H3) and four mitochondrial (12S, 16S, NADH1, and COI) loci. Our phylogenetic analyses cover 133 (125 described and 8 as yet undescribed) grassland species of Pardosa using Trochosa ruricola (De Geer, 1778) and Lycosa coelestis L. Koch, 1878, as outgroups. The results show that our selection of species in the genus is divided into four major clades: Clade I includes only P. crassipalpis Purcell, 1903, from South Africa; Clade II consists of a north-east African group (2 species) and a south-east Asian group (21 species); Clade III contains only P. sutherlandi (Gravely, 1924) from SE Asia; and Clade IV includes five species groups from Asia, Europe, and the Americas. The spiders of the genus probably originated in southern Africa or southern and eastern (SE) Asia at the Middle Miocene Climatic Optimum, about 19.40–14.18 Ma, and then expanded northwards to North America via the Bering Strait, as well as southwards to north-east Africa via the Arabian Peninsula, and westwards to Europe via western Asia between about 10.59 and 5.28 Ma. At least three exchanges occurred between North America and SE Asia, and at least two between Europe and North America. The biogeography of Pardosa in the past 14.18 Ma, associated with the evolution of grasses, suggested a late Cenozoic diversification of the genus as grasslands expanded. [ABSTRACT FROM AUTHOR]